Data Labeling
Data labeling is the process of tagging data to train machine learning models. We review a range of data labeling tools and services, from audio annotation to image classification, to support AI development.
Human Annotated Data in 2025
As the AI market grows (Figure 1), integrating AI solutions remains challenging due to time-consuming tasks like data collection and annotation. Many use automated annotation tools to streamline the tedious process of data annotation, but robust machine learning models still require human-in-the-loop approaches and human-annotated data.
Data Labeling for Natural Language Processing (NLP) in 2025
Have you ever asked Siri to solve a math problem? Or asked about the weather from your Google assistant? Or have you used a sentence correction tool on your computer? If yes, then you have used natural language processing (NLP). NLP technology is increasingly being used to enable smart communication between people and their devices.
Intent Classification in 2025: What it is & How it Works
Customers have more options than ever due to increasing competition and the quality of customer service has become one of the key factors for businesses to stay ahead of the competition. This article, we will explore one of the techniques used in these applications: intent classification.
Audio Annotation in 2025
A subset of data annotation, audio annotation, is a critical technique for building well-performing natural language processing (NLP) models. These models offer numerous benefits to organizations, including analyzing text, speeding up customer responses, and recognizing human emotions. In this article, we take a deep dive into audio annotation to understand its importance for businesses.
Top 20 Data Labeling Tools in August 2025
Data labeling, the process of annotating raw data (such as images, text or audio), is essential for training ML models to perform tasks like classification and recognition. Here, we introduce top 20 data labeling tools. The top data labeling tools: Ranking: From most to least comprehensive.
10 Open Source Data Labeling Platforms in 2025
Data labeling, the process of annotating raw data (such as images, text, or audio), is essential for training ML models to perform tasks like classification and recognition. While pre-built solutions exist, they may not always meet specific needs, making open-source platforms a more flexible and customizable alternative. See the top 10 open-source data labeling tools.